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Qualifications PhD degree in computer science, data science, or related fields. Effective written and verbal communication skills Robust machine learning and natural language processing skills Proficient computer
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thriving community of researchers working in related subject areas. You will design and conduct research into human behaviour (habits, learning under uncertainty) that is of an international standard, and
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metabolism Strong problem-solving skills and the ability to develop novel computational methods for data integration and analysis Experience with machine learning approaches for biological data modeling and
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. Teaching may also be included, but up to no more than 20% of working hours. The position includes the opportunity for three weeks of training in higher education teaching and learning. The purpose
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and setup: Within the project, we follow a multidisciplinary collaborative approach for which we are have recruited 3 PhD students focusing on material science, advanced in vivo imaging and computation
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psychoactive substances, in seized drug products or clinical samples. The candidate will have the opportunity to work directly with experimentalists to validate predictions made by their machine-learning models
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, learning under uncertainty) that is of an international standard, and that is carried out expertly, rigorously and in accordance with ethical guidelines. You will also participate actively in the lab
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appointment involves developing instrumental methods for enhancing proteins, especially plant proteins, functionalities and application in food products. Experience and willingness to learn Proteomics and/or
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, unlocking reliable perception and navigation where GNSS/GPS cannot be trusted or is unavailable. The project combines ultrasonic sensing, probabilistic perception, and machine learning with advanced robotics
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measurements are most informative and guiding where, when and how to observe next. By combining Bayesian inference, probabilistic modeling, and machine learning, the project aims to make Arctic observations more